Optimizing communication in air-ground robot networks using decentralized control
We develop a distributed controller to position a team of aerial vehicles in a configuration that optimizes communication-link quality, to support a team of ground vehicles performing a collaborative task.We propose a gradient-based control approach where agents' positions locally minimize a ph...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021
|
| Online Access: | https://hdl.handle.net/1721.1/137930 |
| _version_ | 1826211077896011776 |
|---|---|
| author | Gil, Stephanie Schwager, Mac Julian, Brian J Rus, Daniela |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Gil, Stephanie Schwager, Mac Julian, Brian J Rus, Daniela |
| author_sort | Gil, Stephanie |
| collection | MIT |
| description | We develop a distributed controller to position a team of aerial vehicles in a configuration that optimizes communication-link quality, to support a team of ground vehicles performing a collaborative task.We propose a gradient-based control approach where agents' positions locally minimize a physically motivated cost function. The contributions of this paper are threefold. We formulate of a cost function that incorporates a continuous, physical model of signal quality, SIR. We develop a non-smooth gradient-based controller that positions aerial vehicles to acheive optimized signal quality amongst all vehicles in the system. This controller is provably convergent while allowing for non-differentiability due to agents moving in or out of communication with one another. Lastly, we guarantee that given certain initial conditions or certain values of the control parameters, aerial vehicles will never disconnect the connectivity graph. We demonstrate our controller on hardware experiments using AscTec Hummingbird quadrotors and provide aggregate results over 10 trials. We also provide hardware-in-the-loop and MATALB simulation results, which demonstrate positioning of the aerial vehicles to minimize the cost function H and improve signal-quality amongst all communication links in the ground/air robot team. ©2010 IEEE. |
| first_indexed | 2024-09-23T15:00:32Z |
| format | Article |
| id | mit-1721.1/137930 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:00:32Z |
| publishDate | 2021 |
| publisher | IEEE |
| record_format | dspace |
| spelling | mit-1721.1/1379302023-02-10T20:11:23Z Optimizing communication in air-ground robot networks using decentralized control Gil, Stephanie Schwager, Mac Julian, Brian J Rus, Daniela Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Lincoln Laboratory We develop a distributed controller to position a team of aerial vehicles in a configuration that optimizes communication-link quality, to support a team of ground vehicles performing a collaborative task.We propose a gradient-based control approach where agents' positions locally minimize a physically motivated cost function. The contributions of this paper are threefold. We formulate of a cost function that incorporates a continuous, physical model of signal quality, SIR. We develop a non-smooth gradient-based controller that positions aerial vehicles to acheive optimized signal quality amongst all vehicles in the system. This controller is provably convergent while allowing for non-differentiability due to agents moving in or out of communication with one another. Lastly, we guarantee that given certain initial conditions or certain values of the control parameters, aerial vehicles will never disconnect the connectivity graph. We demonstrate our controller on hardware experiments using AscTec Hummingbird quadrotors and provide aggregate results over 10 trials. We also provide hardware-in-the-loop and MATALB simulation results, which demonstrate positioning of the aerial vehicles to minimize the cost function H and improve signal-quality amongst all communication links in the ground/air robot team. ©2010 IEEE. 2021-11-09T15:45:11Z 2021-11-09T15:45:11Z 2010-05 2019-07-10T13:53:20Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137930 Gil, Stephanie, Schwager, Mac, Julian, Brian J and Rus, Daniela. 2010. "Optimizing communication in air-ground robot networks using decentralized control." en 10.1109/robot.2010.5509622 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf IEEE MIT web domain |
| spellingShingle | Gil, Stephanie Schwager, Mac Julian, Brian J Rus, Daniela Optimizing communication in air-ground robot networks using decentralized control |
| title | Optimizing communication in air-ground robot networks using decentralized control |
| title_full | Optimizing communication in air-ground robot networks using decentralized control |
| title_fullStr | Optimizing communication in air-ground robot networks using decentralized control |
| title_full_unstemmed | Optimizing communication in air-ground robot networks using decentralized control |
| title_short | Optimizing communication in air-ground robot networks using decentralized control |
| title_sort | optimizing communication in air ground robot networks using decentralized control |
| url | https://hdl.handle.net/1721.1/137930 |
| work_keys_str_mv | AT gilstephanie optimizingcommunicationinairgroundrobotnetworksusingdecentralizedcontrol AT schwagermac optimizingcommunicationinairgroundrobotnetworksusingdecentralizedcontrol AT julianbrianj optimizingcommunicationinairgroundrobotnetworksusingdecentralizedcontrol AT rusdaniela optimizingcommunicationinairgroundrobotnetworksusingdecentralizedcontrol |